package org.example


import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.functions.desc
import org.apache.spark.sql.types.{IntegerType, StringType, StructField, StructType}

object yun209 {
  def main(args: Array[String]): Unit = {
    val spark = SparkSession
      .builder()
      .master("local[*]")
      .appName("spark")
      .getOrCreate()
    val sc = spark.sparkContext

    val schemaUser = StructType(Seq(
      StructField("id", IntegerType),
      StructField("gender", StringType),
      StructField("age", IntegerType),
      StructField("occupation", IntegerType),
      StructField("location", StringType)
    ))
    val user =spark.read.option("sep","::").schema(schemaUser)
      .csv("src/main/resources/users.dat")
    user.show(5)
    //1.查询替换where/filter
    user.where("gender='F'and age = 18").show(3)
    user.filter("gender='F'and age = 18").show(3)
    spark.udf.register("replace",(x:String) =>{
      x match {
        case "M" => 0
        case "F" => 1
      }
    })
    user.selectExpr("id","replace(gender) as sexual","age").show(3)
    user.select("id","age","location").show(3)
    //2.排序orderBy sort
    user.orderBy(desc("age")).show(5)
    user.sort(-user("id")).show(5)
    //3.分组
    user.groupBy("gender").count().show()
    //4.连接join(DataFrame,"列名","连接方式left_outer")

    //5.练习:求18岁女生评分电影为5分的所有电影名



    sc.stop()
  }

}
